Twitter X Reply Scraper

Twitter X Reply Scraper

The Twitter X Reply Scraper collects “Latest” search results from X (Twitter) and extracts direct replies for each post at scale. It solves the challenge of capturing conversation context by combining tweet discovery with reply harvesting — ideal for marketers, developers, data analysts, and researchers who need a reliable Twitter reply scraper or X replies extractor. Use it as a tweet replies scraper for social listening, a Twitter conversation thread scraper for brand monitoring, or a Twitter reply crawler for customer support analytics — all streamlined into a structured dataset for CSV/JSON export.

What data / output can you get?

Below are the exact fields this actor saves to your dataset for each post (plus nested replies):

Data type	Description	Example value
tweetLink	Direct link to the post	https://x.com/example/status/1779999999999999999
avatar	Profile image URL (upsized from “_normal” to “_bigger” when available)	https://pbs.twimg.com/profile_images/..._bigger.jpg
fullname	Display name of the author	Jane Doe
handle	Handle of the author (with @)	@janedoe
verified	Whether the author is verified (true/false or null)	true
tweetDate	ISO-like timestamp from X “created_at”	2026-04-20T15:42:00.000Z
tweetContent	Full text of the post	Excited to launch our new product today!
commentCount	Reply count shown on the post	42
retweetCount	Retweet count	15
quoteCount	Quote tweet count	3
likeCount	Like (favorite) count	128
repliesData	Array of direct reply objects (same structure as above, without nested replies)	[ { reply object }, ... ]

Notes:

• repliesData contains only direct replies to the focal tweet (where in_reply_to_status_id_str matches the tweet).
• Export your dataset to CSV or JSON directly from Apify.

Key features

• 🔎 Latest results + direct replies extraction Uses X GraphQL SearchTimeline to find posts in the “Latest” tab, then loads direct replies per post via TweetDetail — perfect for scrape Twitter replies workflows and conversation analysis.

• 🧠 Dynamic GraphQL & transaction handling Automatically resolves dynamic query IDs from X’s main JS bundle and generates x-client-transaction-id headers for resilient, accurate calls to SearchTimeline and TweetDetail.

• 🧵 Conversation-aware reply parsing Captures direct replies by matching the in_reply_to relation, returning clean, per-post threads in repliesData. Ideal as a Twitter thread replies downloader or Twitter replies extractor.

• 📈 Scale with limits & pagination Control collection with maxSearchResults (per search link) and maxReplies (per post). The actor paginates via cursors to cover long “Latest” timelines reliably.

• 🌐 Smart connectivity with proxies Choose to start with direct connections or enable Apify Proxy. The actor escalates automatically (direct → DC → Residential) when connection blocks are detected.

• 💾 Streamed dataset output Each post (with its repliesData) is pushed to the dataset as it’s processed — great for incremental pipelines, dashboards, or Twitter replies export CSV.

• 💻 Developer-friendly integration Run via Apify’s API and connect with Python or automation tools. Use it as a Twitter replies API scraper component in your data workflows.

• 🔐 Session-based, no API keys required Works with your X session (authToken + ct0). No official API keys needed — a practical X replies scraper without API keys for authenticated, public content access.

• ⚙️ Production-ready reliability Built on Apify infrastructure with structured logs, retry logic, and header/cookie management. Optimized for consistent, large-scale runs.

How to use Twitter X Reply Scraper - step by step

1. Create or log in to your Apify account.
2. Open the Twitter X Reply Scraper actor.
3. Add Start URLs:
   • Paste one or more X search URLs (e.g., https://x.com/search?q=%23yourtopic&src=typed_query&f=live). The q parameter is parsed automatically.
4. Provide your session:
   • Enter authToken and ct0 from your X (Twitter) session. These are required for the actor to access public content with your account.
5. Set limits:
   • maxSearchResults controls how many posts to collect per search link.
   • maxReplies limits how many direct replies to save for each post.
6. (Optional) Configure proxy:
   • Set proxyConfiguration.useApifyProxy to true if you prefer routing through Apify Proxy from the start. Otherwise, the actor begins direct and escalates on blocks.
7. Run the actor:
   • Click Start. The actor loads “Latest” results, follows pagination, and pushes each post with repliesData to the dataset as it goes.
8. Export results:
   • Go to the Dataset tab to browse, then export to CSV or JSON for analysis and reporting.

Pro Tip: Automate social listening or support tagging by triggering this Twitter reply scraper tool via the Apify API and sending the dataset to your BI stack or CRM. Perfect for Twitter replies export CSV pipelines.

Use cases

Use case name	Description
Brand monitoring + reply analysis	Track brand mentions and scrape Twitter replies to measure sentiment, spot issues, and surface customer insights across conversation threads.
Social listening for campaigns	Analyze “Latest” timelines for keywords/hashtags to understand audience feedback and top replies during launches or events with a tweet replies scraper.
Customer support triage	Pull direct replies to product announcements to identify bugs, feature requests, and support questions quickly.
Competitive research	Monitor competitor posts and replies to benchmark engagement patterns and recurring themes using an X reply scraper.
Content strategy optimization	Use reply-level feedback and counts to refine messaging based on what resonates most with your audience.
Academic & policy research	Collect structured conversation data for studies on discourse, virality, and community behavior with a Twitter replies extractor.
Data pipelines / API enrichment	Integrate as a Twitter replies API scraper component in ETL jobs; export JSON for downstream NLP, clustering, or dashboards.

Why choose Twitter X Reply Scraper?

The Twitter X Reply Scraper is built for precision, scale, and workflow automation — a production-ready alternative to brittle browser add-ons.

• ✅ Accurate, conversation-aware extraction: Direct replies are identified via in_reply_to relationships.
• 🌍 Scalable & resilient: Cursor-based pagination, dynamic query IDs, and x-client-transaction-id ensure consistent runs.
• 🔌 Developer access: Integrate via Apify’s API, schedule runs, and plug results into Python or no-code tools.
• 🧩 CSV/JSON outputs: Clean, structured exports for dashboards, analytics, or CRM enrichment.
• 🌐 Proxy-ready reliability: Optional Apify Proxy with automatic escalation on blocks.
• 🔐 Safe by design: Uses your own X session (authToken + ct0), avoiding the need for official API keys.
• 💸 Cost-effective vs. extensions: More stable and maintainable than ad hoc browser-based tools.

In short, it’s the reliable X reply scraper you can run at scale for consistent, structured results.

Is it legal / ethical to use Twitter X Reply Scraper?

Yes — when used responsibly. This actor accesses publicly available content on X (Twitter) using your authenticated session.

Guidelines:

• Only collect data that is publicly visible to your account.
• Review and respect X’s Terms of Service and robots rules.
• Ensure compliance with data protection laws (e.g., GDPR, CCPA) and your internal policies.
• Use the data for legitimate purposes; avoid misuse or spam.
• Consult your legal team if you have specific compliance questions.

Input parameters & output format

Example JSON input

{
  "startUrls": [
    "https://x.com/search?q=%23journorequest+min_replies%3A10&src=typed_query&f=live"
  ],
  "maxSearchResults": 10,
  "maxReplies": 5,
  "authToken": "YOUR_AUTH_TOKEN",
  "ct0": "YOUR_CT0",
  "proxyConfiguration": {
    "useApifyProxy": false
  }
}

Parameters

Name	Type	Description	Default	Required
startUrls	array	Add one or more X search page links (the same URLs you get when you search on x.com). Each link defines what topic or keywords you want to follow.	—	Yes
maxSearchResults	integer	Choose how many posts you want from each search link — higher numbers give you a broader snapshot; lower numbers finish faster.	10	No
maxReplies	integer	For each post found, decide how many replies to keep in your results.	5	No
authToken	string	Your X account session token (or set the AUTH_TOKEN environment variable in Apify).	""	No
ct0	string	The companion security value for your X session (or use the CT0 env var).	""	No
proxyConfiguration	object	Optional Apify Proxy settings for smoother runs in the cloud. Off by default; enable when it suits you.	{"useApifyProxy": false}	No

Notes:

• Both authToken and ct0 are required at runtime. If not provided in input, the actor reads AUTH_TOKEN and CT0 from environment variables.
• startUrls should be X “Latest” search URLs; the q parameter is parsed automatically.

Example JSON output

[
  {
    "tweetLink": "https://x.com/acme/status/1780012345678900000",
    "avatar": "https://pbs.twimg.com/profile_images/1234567890/abc_bigger.jpg",
    "fullname": "ACME Inc.",
    "handle": "@acme",
    "verified": true,
    "tweetDate": "2026-04-20T12:30:00.000Z",
    "tweetContent": "We’re excited to share our new update! 🚀",
    "commentCount": 27,
    "retweetCount": 12,
    "quoteCount": 2,
    "likeCount": 103,
    "repliesData": [
      {
        "tweetLink": "https://x.com/janedoe/status/1780012345678901111",
        "avatar": "https://pbs.twimg.com/profile_images/2222222222/def_bigger.jpg",
        "fullname": "Jane Doe",
        "handle": "@janedoe",
        "verified": false,
        "tweetDate": "2026-04-20T12:35:00.000Z",
        "tweetContent": "Congrats! Looking forward to trying it out.",
        "commentCount": 1,
        "retweetCount": 0,
        "quoteCount": 0,
        "likeCount": 5
      }
    ]
  }
]

Field notes:

• verified may be null if not available.
• avatar may be empty if not resolvable.
• repliesData includes only direct replies to the focal tweet.

FAQ

Do I need to log in or provide cookies?

✅ Yes. Provide your X session values via authToken and ct0 in the input, or set AUTH_TOKEN and CT0 as environment variables. The actor uses your session to access publicly visible content.

Does this use the official Twitter API?

❌ No official API keys are required. The actor calls X’s GraphQL endpoints (SearchTimeline and TweetDetail) with your session and generated headers, working as a Twitter replies API scraper without API keys.

What kind of replies does it collect?

🧵 It collects direct replies to each focal tweet (where in_reply_to matches the tweet). These replies are returned in repliesData for each post.

How many posts and replies can I scrape?

📈 You can collect up to maxSearchResults (1–5000) posts per search URL and up to maxReplies (1–500) replies per post. Set these in the input to match your needs.

Can I export the results?

💾 Yes. Open the Dataset for your run and export to CSV or JSON. This makes it easy to plug into analytics pipelines or share with stakeholders.

Can I use proxies?

🌐 Yes. You can enable Apify Proxy via proxyConfiguration.useApifyProxy. The actor also escalates connectivity from direct to DC and then to Residential proxies when blocks are detected.

Does it work with Python or automation tools?

💻 Yes. Trigger the actor via Apify’s API, integrate with your Python scripts, or orchestrate runs with tools like Make or n8n. It’s built to slot into data pipelines as a Twitter reply scraper Python-friendly component.

Is it legal to scrape Twitter/X with this tool?

🛡️ Yes, when done responsibly. Only collect publicly visible content, comply with X’s terms and applicable regulations (e.g., GDPR/CCPA), and use the data ethically. Consult your legal team for specific use cases.

Closing CTA / Final thoughts

The Twitter X Reply Scraper is built to capture “Latest” posts and their direct replies in a clean, structured format. With session-based access, dynamic GraphQL handling, proxy resilience, and CSV/JSON exports, it’s ideal for marketers, analysts, developers, and researchers who need a dependable X reply scraper.

Run it on Apify to automate social listening, brand monitoring, and research — or call it via API from your Python workflows to power Twitter replies export CSV pipelines. Start extracting smarter, conversation-aware insights from X at scale.